FENNEC: Functional Exploration of Natural Networks and Ecological Communities

Assessment of species composition in ecological communities and networks is an important aspect of biodiversity research. Yet, for many ecological questions the ecological properties (traits) of organisms in a community are more informative than their scientific names. Furthermore, other properties like threat status, invasiveness, or human usage are relevant for many studies, but they can not be directly evaluated from taxonomic names alone. Despite the fact that various public databases collect such trait information, it is still a tedious manual task to enrich existing community tables with those traits, especially for large data sets. For example, nowadays, meta-barcoding or automatic image processing approaches are designed for high-throughput analyses, yielding thousands of taxa for hundreds of samples in very short time frames.

We developed the FENNEC, a web-based workbench that eases this process by mapping publicly available trait data to the user’s community tables in an automated process. We run a public instance holding traits that cover a range of topics includeing specialization, invasiveness, vulnerability, and agricultural relevance. Scientists are free to use the FENNEC as a resource for their ecological research.

Website: https://fennec.molecular.eco

Freely available at GitHub:  https://github.com/molbiodiv/fennec

Preprint: https://www.biorxiv.org/content/early/2017/09/27/194308

TBro: visualization and management of de novo transcriptomes

A web based transcriptome browser suitable for de novo transcriptomics. It has been used to analyze the Venus Flytrap transcriptome.

TBro is a web application that allows biologists to browse the vast amount of data generated by RNA-seq experiments. Powerful search options exist to find transcripts of interest. All information for each transcript is aggregated on a single page. Transcripts of interest can be organized in carts and analyzed together.

Freely available at GitHub:  https://github.com/TBroTeam/TBro

Publication: https://academic.oup.com/database/article/doi/10.1093/database/baw146/2742073